2023 Global Engineering Frontiers | Cyber-Physical Security of Industrial Control Systems

Industrial Control Systems (ICS) are systems composed of various automation acquisition, monitoring, and control components used for the automated operation and supervision of industrial infrastructure. ICS are mainly divided into data acquisition and monitoring systems, distributed control systems, and programmable logic controllers. Currently, ICS has become the neural hub and operational center of critical national infrastructure such as industrial production, smart grids, and intelligent transportation. Due to the importance and open connectivity of ICS, they have become one of the primary targets for malicious threats. With the continuous improvement of attackers’ vulnerability discovery capabilities and attack techniques, the issue of cyber-physical security in ICS has become increasingly severe. This mainly refers to the security dilemma of “what you see is not what you get, and what you get is not what you do” caused by attackers utilizing the cyber-physical fusion characteristics of ICS to implement coordinated attacks in both the information and physical domains. For example, attackers can penetrate isolation, use intrusion detection, and other information security methods to bypass physical security mechanisms such as redundancy, fault tolerance, and safety chains, conducting precise strikes on ICS across the system monitoring layer, control layer, and execution layer. This type of cyber-physical fusion security threat not only has the potential to “penetrate” information security defenses but can also leverage the business characteristics of ICS to design malicious data tampering and deception mechanisms that are highly cooperative and concealed. This poses a significant challenge to the security protection of ICS.

Currently, research related to cyber-physical security in ICS mainly focuses on the following three areas: ① Attacker capability modeling/system vulnerability analysis, which involves designing attack strategies from the perspective of attackers targeting the architecture, protocols, and controls of ICS to construct attacker models and achieve vulnerability analysis of ICS; ② Attack detection, which involves passively collecting dynamic operational data from the system or actively adding dynamic authentication information to construct normal operational characteristic modes for detecting malicious attack behaviors; ③ Attack defense, which includes identifying malicious attack nodes, mobile target defense, and resilient security control strategies. In the future, further vulnerability analysis and security protection research will be conducted focusing on the large-scale, multi-level, and highly coupled characteristics of ICS to achieve an upgrade in the protection of ICS.

This frontier topic includes the number and annual publication status of core papers published between 2017 and 2022 (Note: The high-impact papers that rank in the top 10% of citation frequency for this topic retrieved from Web of Science as of January 2023) as shown in Tables 1.1.1 and 1.1.2.

He Jianping, Associate Professor with Tenure Track at the Department of Automation, Shanghai Jiao Tong University, Doctoral Supervisor, selected as a2018 National Young Top Talent.In November 2013, he obtained a Ph.D. in Engineering from Zhejiang University, and from2014 to2017 he conducted postdoctoral research at the University of Victoria, Canada. His main research directions include distributed learning, control and optimization, security and privacy foundational theory, multi-robot intelligent systems, and industrial big data. He has published over40 long papers in journals such asIEEE TIT, IEEE TAC, IEEE TDSC, Automatica.He is currently an associate editor forIEEE Trans Contr Network Syst, KSII Trans Int Inform Syst, andIEEE Open J Veh Technol, and has served as a guest editor for journals such asIEEE Trans Autom Contr, IEEE Tran Ind Inform.He has received numerous honors including the2015 Excellent Doctoral Dissertation Award from the Chinese Association of Automation, the Ministry of Education’s First Prize for Natural Science, theIEEE WCSP 2017 Best Paper Award, theIEEE PESGM 2017 Best Conference Paper Award, and nominations for the Best Student Paper Award atIEEE ICCA 2017 andIEEE VTC2020-Fall.

Fang Chongrong, Assistant Professor with Tenure Track at the Department of Automation, Shanghai Jiao Tong University, Doctoral Supervisor, primarily engaged in research on the security of cyber-physical systems and abnormal detection and diagnosis in cloud networks, having published multiple papers inIEEE TAC,Automatica,IEEE/ACM ToN,ACM SIGCOMM. He received the2023 First Prize for Scientific and Technological Progress from the Chinese Association of Automation, the2021 First Prize for Technological Invention from the Chinese Computer Society, and has led National Fund for Young Scientists projects.

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